1 Histogramas - R Base

## [1] -0.01330762
##   location      value
## 1      col -1.8719792
## 2      col -0.3383812
## 3      col  0.3548935
## 4      col  1.6680366
## 5      col -0.2856015
## 6      col -1.3252798
## 'data.frame':    1000 obs. of  2 variables:
##  $ location: chr  "col" "col" "col" "col" ...
##  $ value   : num  -1.872 -0.338 0.355 1.668 -0.286 ...

2 Histogramas - ggplot

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.3     ✓ purrr   0.3.4
## ✓ tibble  3.0.6     ✓ dplyr   1.0.4
## ✓ tidyr   1.1.2     ✓ stringr 1.4.0
## ✓ readr   1.4.0     ✓ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
##   location      value
## 1      col -1.8719792
## 2      col -0.3383812
## 3      col  0.3548935
## 4      col  1.6680366
## 5      col -0.2856015
## 6      col -1.3252798
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

##   location      value
## 1      col -1.8719792
## 2      col -0.3383812
## 3      col  0.3548935
## 4      col  1.6680366
## 5      col -0.2856015
## 6      col -1.3252798

##   location      value
## 1      col -1.0822942
## 2      col -1.4719386
## 3      col -2.2040994
## 4      col  0.3562852
## 5      col -1.7147851
## 6      col -0.4913932
##      location    value
## 1995     peru 3.133988
## 1996     peru 3.650295
## 1997     peru 4.134690
## 1998     peru 2.449526
## 1999     peru 4.631226
## 2000     peru 4.739639
## [1] 2000    2

3 Densidades

##   location      value
## 1      col -1.8719792
## 2      col -0.3383812
## 3      col  0.3548935
## 4      col  1.6680366
## 5      col -0.2856015
## 6      col -1.3252798

4 Densidades con 2 set de datos

##   location      value
## 1      col -1.0822942
## 2      col -1.4719386
## 3      col -2.2040994
## 4      col  0.3562852
## 5      col -1.7147851
## 6      col -0.4913932

## 
## Attaching package: 'gridExtra'
## The following object is masked from 'package:dplyr':
## 
##     combine

##     colombia       peru argentina        us    brasil
## 1 -11.186951 -35.814125  39.20946 104.60548 102.61603
## 2   9.020724 -34.978722 -40.59333 162.99971 142.77937
## 3   5.864960  21.674366  34.05761  39.80808  71.36377
## 4  -6.035194   8.437587 -74.27318  75.57745  70.20479
## 5  -1.157605  19.558368 -11.67167 125.23552 172.42622
## 6  -1.504274  21.438675 -16.80262  56.71725 100.80200

5 Graficas de dispersión

##     colombia       peru argentina        us    brasil
## 1 -11.186951 -35.814125  39.20946 104.60548 102.61603
## 2   9.020724 -34.978722 -40.59333 162.99971 142.77937
## 3   5.864960  21.674366  34.05761  39.80808  71.36377
## 4  -6.035194   8.437587 -74.27318  75.57745  70.20479
## 5  -1.157605  19.558368 -11.67167 125.23552 172.42622
## 6  -1.504274  21.438675 -16.80262  56.71725 100.80200
## [1] 100
## [1] 100   5
##     colombia       peru argentina        us    brasil
## 1 -11.186951 -35.814125  39.20946 104.60548 102.61603
## 2   9.020724 -34.978722 -40.59333 162.99971 142.77937
## 3   5.864960  21.674366  34.05761  39.80808  71.36377
## 4  -6.035194   8.437587 -74.27318  75.57745  70.20479
## 5  -1.157605  19.558368 -11.67167 125.23552 172.42622
## 6  -1.504274  21.438675 -16.80262  56.71725 100.80200
##     colombia       peru argentina        us    brasil year
## 1 -11.186951 -35.814125  39.20946 104.60548 102.61603 2018
## 2   9.020724 -34.978722 -40.59333 162.99971 142.77937 2019
## 3   5.864960  21.674366  34.05761  39.80808  71.36377 2020
## 4  -6.035194   8.437587 -74.27318  75.57745  70.20479 2021
## 5  -1.157605  19.558368 -11.67167 125.23552 172.42622 2018
## 6  -1.504274  21.438675 -16.80262  56.71725 100.80200 2019
## 'data.frame':    100 obs. of  6 variables:
##  $ colombia : num  -11.19 9.02 5.86 -6.04 -1.16 ...
##  $ peru     : num  -35.81 -34.98 21.67 8.44 19.56 ...
##  $ argentina: num  39.2 -40.6 34.1 -74.3 -11.7 ...
##  $ us       : num  104.6 163 39.8 75.6 125.2 ...
##  $ brasil   : num  102.6 142.8 71.4 70.2 172.4 ...
##  $ year     : int  2018 2019 2020 2021 2018 2019 2020 2021 2018 2019 ...

## 'data.frame':    100 obs. of  6 variables:
##  $ colombia : num  -11.19 9.02 5.86 -6.04 -1.16 ...
##  $ peru     : num  -35.81 -34.98 21.67 8.44 19.56 ...
##  $ argentina: num  39.2 -40.6 34.1 -74.3 -11.7 ...
##  $ us       : num  104.6 163 39.8 75.6 125.2 ...
##  $ brasil   : num  102.6 142.8 71.4 70.2 172.4 ...
##  $ year     : Factor w/ 4 levels "2018","2019",..: 1 2 3 4 1 2 3 4 1 2 ...

## `geom_smooth()` using formula 'y ~ x'

## `geom_smooth()` using formula 'y ~ x'

6 Ahora combinemoslas!!!!!!!!

## 'data.frame':    100 obs. of  6 variables:
##  $ colombia : num  -11.19 9.02 5.86 -6.04 -1.16 ...
##  $ peru     : num  -35.81 -34.98 21.67 8.44 19.56 ...
##  $ argentina: num  39.2 -40.6 34.1 -74.3 -11.7 ...
##  $ us       : num  104.6 163 39.8 75.6 125.2 ...
##  $ brasil   : num  102.6 142.8 71.4 70.2 172.4 ...
##  $ year     : Factor w/ 4 levels "2018","2019",..: 1 2 3 4 1 2 3 4 1 2 ...
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'
## `geom_smooth()` using formula 'y ~ x'

7 Boxplots

##     colombia       peru argentina        us    brasil year
## 1 -11.186951 -35.814125  39.20946 104.60548 102.61603 2018
## 2   9.020724 -34.978722 -40.59333 162.99971 142.77937 2019
## 3   5.864960  21.674366  34.05761  39.80808  71.36377 2020
## 4  -6.035194   8.437587 -74.27318  75.57745  70.20479 2021
## 5  -1.157605  19.558368 -11.67167 125.23552 172.42622 2018
## 6  -1.504274  21.438675 -16.80262  56.71725 100.80200 2019
##   year location      value
## 1 2018 colombia -11.186951
## 2 2019 colombia   9.020724
## 3 2020 colombia   5.864960
## 4 2021 colombia  -6.035194
## 5 2018 colombia  -1.157605
## 6 2019 colombia  -1.504274
## [1] 500   3

##   year location      value
## 1 2018 colombia -11.186951
## 2 2019 colombia   9.020724
## 3 2020 colombia   5.864960
## 4 2021 colombia  -6.035194
## 5 2018 colombia  -1.157605
## 6 2019 colombia  -1.504274
## 'data.frame':    500 obs. of  3 variables:
##  $ year    : Factor w/ 4 levels "2018","2019",..: 1 2 3 4 1 2 3 4 1 2 ...
##  $ location: chr  "colombia" "colombia" "colombia" "colombia" ...
##  $ value   : num  -11.19 9.02 5.86 -6.04 -1.16 ...
## 'data.frame':    500 obs. of  3 variables:
##  $ year    : Factor w/ 4 levels "2018","2019",..: 1 2 3 4 1 2 3 4 1 2 ...
##  $ location: Factor w/ 5 levels "argentina","brasil",..: 3 3 3 3 3 3 3 3 3 3 ...
##  $ value   : num  -11.19 9.02 5.86 -6.04 -1.16 ...

8 Correlaciones

## Registered S3 method overwritten by 'GGally':
##   method from   
##   +.gg   ggplot2
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

## Warning in ggcorr(data3, method = c("everything", "pearson")): data in column(s)
## 'year' are not numeric and were ignored

##     colombia       peru argentina        us    brasil year
## 1 -11.186951 -35.814125  39.20946 104.60548 102.61603 2018
## 2   9.020724 -34.978722 -40.59333 162.99971 142.77937 2019
## 3   5.864960  21.674366  34.05761  39.80808  71.36377 2020
## 4  -6.035194   8.437587 -74.27318  75.57745  70.20479 2021
## 5  -1.157605  19.558368 -11.67167 125.23552 172.42622 2018
## 6  -1.504274  21.438675 -16.80262  56.71725 100.80200 2019
## 'data.frame':    100 obs. of  6 variables:
##  $ colombia : num  -11.19 9.02 5.86 -6.04 -1.16 ...
##  $ peru     : num  -35.81 -34.98 21.67 8.44 19.56 ...
##  $ argentina: num  39.2 -40.6 34.1 -74.3 -11.7 ...
##  $ us       : num  104.6 163 39.8 75.6 125.2 ...
##  $ brasil   : num  102.6 142.8 71.4 70.2 172.4 ...
##  $ year     : Factor w/ 4 levels "2018","2019",..: 1 2 3 4 1 2 3 4 1 2 ...

## corrplot 0.84 loaded
## 'data.frame':    100 obs. of  6 variables:
##  $ colombia : num  -11.19 9.02 5.86 -6.04 -1.16 ...
##  $ peru     : num  -35.81 -34.98 21.67 8.44 19.56 ...
##  $ argentina: num  39.2 -40.6 34.1 -74.3 -11.7 ...
##  $ us       : num  104.6 163 39.8 75.6 125.2 ...
##  $ brasil   : num  102.6 142.8 71.4 70.2 172.4 ...
##  $ year     : Factor w/ 4 levels "2018","2019",..: 1 2 3 4 1 2 3 4 1 2 ...
##             colombia       peru  argentina         us     brasil
## colombia   1.0000000  0.8015215  0.4913152 -0.5146297 -0.6879268
## peru       0.8015215  1.0000000  0.4161253 -0.5147450 -0.6510829
## argentina  0.4913152  0.4161253  1.0000000 -0.1693722 -0.3159770
## us        -0.5146297 -0.5147450 -0.1693722  1.0000000  0.4635345
## brasil    -0.6879268 -0.6510829 -0.3159770  0.4635345  1.0000000

##              [,1]         [,2]         [,3]         [,4]         [,5]
## [1,] 0.000000e+00 1.297798e-23 2.099041e-07 4.315180e-08 2.641572e-15
## [2,] 1.297798e-23 0.000000e+00 1.663033e-05 4.280265e-08 2.238362e-13
## [3,] 2.099041e-07 1.663033e-05 0.000000e+00 9.206154e-02 1.362356e-03
## [4,] 4.315180e-08 4.280265e-08 9.206154e-02 0.000000e+00 1.193377e-06
## [5,] 2.641572e-15 2.238362e-13 1.362356e-03 1.193377e-06 0.000000e+00

9 MAPASSSSSSS

10 Mucho mas!!!!

## Downloading GitHub repo lchiffon/wordcloud2@HEAD
## 
##   
   checking for file ‘/private/var/folders/g8/1mnmhw097xlf33x526dsppbm0000gn/T/RtmpWeBjkF/remotes43de151a0137/Lchiffon-wordcloud2-8a12a3b/DESCRIPTION’ ...
  
✓  checking for file ‘/private/var/folders/g8/1mnmhw097xlf33x526dsppbm0000gn/T/RtmpWeBjkF/remotes43de151a0137/Lchiffon-wordcloud2-8a12a3b/DESCRIPTION’
## 
  
─  preparing ‘wordcloud2’:
## 
  
   checking DESCRIPTION meta-information ...
  
✓  checking DESCRIPTION meta-information
## 
  
─  checking for LF line-endings in source and make files and shell scripts
## 
  
─  checking for empty or unneeded directories
##    Removed empty directory ‘wordcloud2/examples/img’
##    Removed empty directory ‘wordcloud2/examples’
## 
  
─  building ‘wordcloud2_0.2.2.tar.gz’
## 
  
   
##